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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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model-index:
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- name: baseline_nli_bert
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# baseline_nli_bert
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9280
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- Accuracy: 0.6063
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- Precision: 0.6063
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- Recall: 0.6063
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- F1 Score: 0.6088
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-06
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 101
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
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| 1.0366 | 1.0 | 2583 | 0.9579 | 0.5603 | 0.5603 | 0.5603 | 0.5638 |
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| 0.9416 | 2.0 | 5166 | 0.9206 | 0.5826 | 0.5826 | 0.5826 | 0.5877 |
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| 0.8889 | 3.0 | 7749 | 0.9085 | 0.5981 | 0.5981 | 0.5981 | 0.6025 |
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| 0.8539 | 4.0 | 10332 | 0.9176 | 0.6054 | 0.6054 | 0.6054 | 0.6089 |
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| 0.8323 | 5.0 | 12915 | 0.9201 | 0.6049 | 0.6049 | 0.6049 | 0.6066 |
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| 0.811 | 6.0 | 15498 | 0.9280 | 0.6063 | 0.6063 | 0.6063 | 0.6088 |
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### Framework versions
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- Transformers 4.27.3
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- Pytorch 1.12.1
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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